Identification of pH process using Hammerstein-Wiener model

Abinayadhevi, P.; Prasad, S. J. Suji

doi:10.1109/isco.2015.7282297

Cited by 8 publications

(1 citation statement)

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“…A change to the traditional technique is provided to stabilize the process during the nonlinear output error model estimation [2]. To ensure the capability and performance of the heat exchanger, the Hammerstein-Wiener model was used to validate the system [3][4][5][6][7][8][9]. The objective of SI is to identify a model that provides satisfactory estimation by choosing the best method from different types of SI in the design of process controllers [10].…”

Section: Introductionmentioning

confidence: 99%

Identification of heat exchanger process through Hammerstein and polynomial models

L D

2024

Phys. Scr.

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Process industries extensively use heat exchangers in their operations, playing a crucial role in various sectors by facilitating efficient heat transfer, conserving energy, and reducing operational costs. This paper focuses on identifying and validating the system model, with the primary task of designing the controller involving the determination of the mathematical representation of the system. The First Order Plus Dead Time (FODT) model, derived from basic principles, is used to represent the system. To analyze the system's behavior and construct a suitable controller, model development is essential, achieved by constructing principles models using energy balance equations to identify the heat exchanger process. Data collected from the model are utilized in the identification process, with the temperature at the outlet of the hot air blower being the controlled variable in this investigation. The research aims to determine the mathematical model based on time versus temperature data acquired from the Heat Exchanger. Various system identification methods, such as Hammerstein Wiener (HW), Auto Regressive with Exogenous Input (ARX), Box-Jenkins (BJ), Output-Error (OE), and Auto Regressive Moving Average with Exogenous Input (ARMAX) models, are implemented for the heat exchanger. The models obtained undergo validation, and the best-fit model closest to the physical system is considered for controller design. After conducting the analysis, it was found that the Output-Error (OE) model outperforms other models in terms of achieving the best fit.

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